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Bayesian block-sparse channel estimation for large-scale MISO-OFDM systems

  • Xi'an Jiaotong University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This letter studies a new method based on Bayesian variational inference to estimate the sparse channel parameters in large-scale multiple-input-single-output orthogonal frequency division multiplexing (MISO-OFDM) systems. Also, the sparse common support of different channel impulse responses, which results in a block- structured model, is considered. The covariance matrix of the block is introduced in the block-structured model to effectively recover the channel parameters combining with the Bayesian hierarchical structure. Furthermore, variational message-passing (VMP) is applied to slove the problem. The simulation results show that the proposed algorithm outperforms the traditional ones.

源语言英语
主期刊名2016 IEEE 83rd Vehicular Technology Conference, VTC Spring 2016 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781509016983
DOI
出版状态已出版 - 5 7月 2016
活动83rd IEEE Vehicular Technology Conference, VTC Spring 2016 - Nanjing, 中国
期限: 15 5月 201618 5月 2016

丛书

姓名IEEE Vehicular Technology Conference
2016-July
ISSN(印刷版)1550-2252

会议

会议83rd IEEE Vehicular Technology Conference, VTC Spring 2016
国家/地区中国
Nanjing
时期15/05/1618/05/16

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